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An Expanded Set of Amino Acid Analogs for the Ribosomal Translation of Unnatural Peptides

Overview of attention for article published in PLOS ONE, October 2007
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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9 X users
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7 patents
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2 Wikipedia pages

Citations

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159 Dimensions

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238 Mendeley
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Title
An Expanded Set of Amino Acid Analogs for the Ribosomal Translation of Unnatural Peptides
Published in
PLOS ONE, October 2007
DOI 10.1371/journal.pone.0000972
Pubmed ID
Authors

Matthew C. T. Hartman, Kristopher Josephson, Chi-Wang Lin, Jack W. Szostak

Abstract

The application of in vitro translation to the synthesis of unnatural peptides may allow the production of extremely large libraries of highly modified peptides, which are a potential source of lead compounds in the search for new pharmaceutical agents. The specificity of the translation apparatus, however, limits the diversity of unnatural amino acids that can be incorporated into peptides by ribosomal translation. We have previously shown that over 90 unnatural amino acids can be enzymatically loaded onto tRNA. We have now used a competition assay to assess the efficiency of tRNA-aminoacylation of these analogs. We have also used a series of peptide translation assays to measure the efficiency with which these analogs are incorporated into peptides. The translation apparatus tolerates most side chain derivatives, a few alpha,alpha disubstituted, N-methyl and alpha-hydroxy derivatives, but no beta-amino acids. We show that over 50 unnatural amino acids can be incorporated into peptides by ribosomal translation. Using a set of analogs that are efficiently charged and translated we were able to prepare individual peptides containing up to 13 different unnatural amino acids. Our results demonstrate that a diverse array of unnatural building blocks can be translationally incorporated into peptides. These building blocks provide new opportunities for in vitro selections with highly modified drug-like peptides.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 3 1%
Germany 1 <1%
South Africa 1 <1%
Unknown 228 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 71 30%
Researcher 55 23%
Student > Bachelor 19 8%
Other 16 7%
Student > Master 16 7%
Other 38 16%
Unknown 23 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 71 30%
Chemistry 61 26%
Biochemistry, Genetics and Molecular Biology 46 19%
Chemical Engineering 8 3%
Pharmacology, Toxicology and Pharmaceutical Science 6 3%
Other 22 9%
Unknown 24 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2023.
All research outputs
#1,972,778
of 25,890,819 outputs
Outputs from PLOS ONE
#23,866
of 225,823 outputs
Outputs of similar age
#4,199
of 85,699 outputs
Outputs of similar age from PLOS ONE
#25
of 230 outputs
Altmetric has tracked 25,890,819 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 225,823 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 85,699 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 230 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.